This invention relates to a method and an apparatus for will determination and bio-signal control, and more particularly to quantifying the will of the human subject to which the apparatus is connected and allowing the subject to control elements of his environment.
Psychologists use electroencephalographic (xe2x80x9cEEGxe2x80x9d) waveforms to interpret the subject""s mental state. This introduces subjective criteria into the analysis because a human expert is required to interpret the EEG waveforms. In addition, to being unable to analyze the subject""s mental state with enough accuracy to determine the subject""s will, this method is labor-intensive and time-consuming.
xe2x80x9cWillxe2x80x9d can be broadly defined to include not only desires and wishes but also emotions. One example of a will is the hunger will and the magnitude of that will. Other wills with magnitudes are the will to scratch one""s arm, to listen to a particular song, etc. Examples of emotions include anger, sadness, joy and disgust. Wills can be further decomposed into sub-wills and magnitudes, for example, such as what kind of and how much food one wishes to eat.
There is a continuing need for means whereby a human subject""s mental state can be decomposed into a, possibly infinite, discrete set of wills and corresponding magnitudes which can be expressed in matrix form. In addition to a host of applications in the human-machine interface field which would benefit from improved will determination, patients suffering with symptoms of such diseases as amyotrophic lateral sclerosis (xe2x80x9cALSxe2x80x9d), who have near-normal mental function but are unable to express their will, would benefit greatly.
Examples of bio-signal control based on monitoring EEG waveforms are described in, for example, Hugh S. Lusted and R. Benjamin Knapp, xe2x80x9cControlling Computers with Neural Signals,xe2x80x9d Scientific American, pages 82-87 (October 1996) and Jonathan R. Wolpaw et al., xe2x80x9cAn EEG-Based Brain-Computer Interface For Cursor Control,xe2x80x9d Electroencephalography and Clinical Neurophysiology, pages 252-259 (March 1991). However, these methods of bio-signal control require training the subject to control the amplitude of a mu wave, a process that may require several days.
In view of the foregoing, it would be desirable to be able to provide a method and an apparatus for will determination and bio-signal control, and more particularly to quantifying the will of the human subject to which the apparatus is connected and allowing the subject to control elements of his environment.
It is an object of this invention to provide a method and an apparatus for will determination and bio-signal control, and more particularly to quantifying the will of the human subject to which the apparatus is connected and allowing the subject to control elements of his environment.
These and other objects of the invention are accomplished in accordance with the principles of the invention by providing a method and an apparatus for will determination and bio-signal control, and more particularly to quantifying the will of the human subject to which the apparatus is connected and allowing the subject to control elements of his environment.
Characteristic values of the subject (i.e., a set of EEG signals which may be supplemented by signals based on a combination of scalp potential, muscle potential, heart-rate, eye-movement and frequency of eye blinks, for example) are detected and corresponding output signals are produced. The output signals are then amplified and digitized. Fourier transformations or cross-correlations are performed on the digitized output signals. A set of state variables is determined for each selected frequency sub-band of a selected frequency band for each of the output signals. Each of the sets of state variables is applied to a trained neural network to determine will of the subject. The will of the subject is then displayed. In order to train the neural network, sets of reference weights and sets of reference biases are formed for a neural network using sets of state reference variables corresponding to known wills.